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Plans for reportLoss after OT ends #298

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tylerdev0 opened this issue Apr 28, 2022 · 4 comments
Open

Plans for reportLoss after OT ends #298

tylerdev0 opened this issue Apr 28, 2022 · 4 comments

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@tylerdev0
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The Fledge spec mentions that win reporting will eventually be moved to some form of aggregate reporting, however the documentation is not clear about auction loss reporting.

I see mentions that the reportLoss functionality may only be available during the initial Origin Trial, however reporting of both wins and losses is critical for bidders to be able to accurately tune bidding models and perform bid shading.

Is there a plan to implement reportLoss in the aggregate reporting long term?

@MattMenke2
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The problem with reportLoss() is it's potentially very heavy weight. Each bidder gets its own process, and there's a FLEDGE process limit, so we would potentially have to spin up new processes and re-load a bunch of bidding scripts at the end of an auction to call reportLoss().

I'm hoping we can add some sort of aggregate reporting calls in generateBid() / scoreAd() to allow reporting if the bid loses instead of adding reportLoss() support, but that does depend on aggregate reporting.

@tylerdev0
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Thanks Matt, your concern makes sense. I think some form of aggregate loss reporting would fulfill our needs - we just need some mechanism to measure how effective our bidding function is which doesn't seem possible without insight into losing bids.

@JensenPaul
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FLEDGE intends to provide mechanisms for losing bidders to learn aggregate outcomes. The Private Aggregation API provides an API for collecting and sending reports for aggregation. I could imagine this API being called from generateBid() or scoreAd(), negating the need for reportLoss(). I could imagine post-auction signals, like winning bid price, being included in the reports via parameterization very similar to what’s offered today for the debug loss and win reporting functions, e.g. you could set the histogram value to ${winningBid} which would be filled in later with the winning bid price. Issue #272 delves more into the area of how to train bidding models using aggregated data, like what comes out of the Private Aggregation API.

@tylerdev0
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Thanks Paul, that is very helpful. I appreciate it.

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